The thrill of AI is fading – and Wall Street is getting clear-eyed about value

Nothing excites and excuses a journalist with opinions more than a volatile stock. Doesn't matter what your opinion is, there's always a change that proves it. Even better: any rapidly changing stock value has to be volatile, so if something is in the news it's probably supporting your position! When you see these claims, ask yourself: How many times has the stock changed in this manner over the last year? How is its current static valuation relative to its long run history? Is the stock in a period of rapid change where higher volatility is expected? Those won't tell you where the stock is headed but they should at least help remind you not to trust horoscopes.

Wall Street is not a reliable proxy for ‘value’.

For the people who judge these innovations by how well they can read their minds and how well it stands up to what people feel they were promised by Star Trek, the last 24 months have been a disappointment.

For those who are becoming far more productive than they previously were, learning new skills, and building the next generation of companies.. that same time has been life changing.

I don’t spend too much time worrying about wall street and I also don’t deny the bottom could fall out, but I have no doubts about the ability of these technologies to dramatically improve lives and be foundational for future improvements.

It's the dotcom boom all over again. Right now the webvans and pets.com of the world are getting insane valuations just by using a .ai tld. When the hubbub dies and the froufrou wash away, the googles, amazons, facebooks that know what they're doing will quietly emerge. Too many hyper-funded startups that are little more than a thin wrapper over foundational LLMs, with dubious usefulness.

Until next-gen models show a drastic improvement in intelligence again. Then the hype will go through the roof once more.

AI shoot to fame with Generative images and Text generation. Found many use cases. For me personally, I have to read a lot less documentation now to Code stuffs.

Apparently emergence of new use-cases is pretty thin. I see many domain specific opportunities, where AI can help. It will take some time to develop software where AI can be purchased and activated for niche company-internal use cases. Till that happens, AI (Neural Network training etc.) are hard core software development problem. Not usable by most of the companies.

The piece itself mostly discusses Nvidia, which is an interesting company from an "AI hype" perspective in that they can only physically produce so many chips, and they are riding a very thin line where their margins are very high and FLOPS (or the equivalent) are in many ways already a commodity, so everyone wants to be set up to compete with them at the first misstep.

Wall Streets idea of value is that the stock price changes within a few months at most, and that is if they are very patient.

Meanwhile getting value from AI means adapting new processes and changing organizations, something that big companies do extremely slowly.

AI that already has obvious value:

- ChatGPT: The OG, most used AI chat. GPT-4/4o/multi-modal is already the prosumer LLM use case - excellent as an office/tech/language/creative assistant. Apparently Open AI's revenue is already in the billions and there's no denying people are using ChatGPT. There are also countless open-source libraries requiring `OPENAI_API_KEY` and many companies allocating budgets for spending there.

- LLM summarization: Amazon is already using LLMs to summarize reviews at the top of their product pages, search engines are using LLMs to summarize results at the top. GitHub has an LLM bot that you used to have to wait days for support to reply for - these are popping up everywhere. These will only improve to save people time and surface the exact information you're looking for. It's changing the way people access information and accomplish basic self-serve customer tasks.

- Customer service: The text-to-speech AI is getting very very good, to the point you can't tell it's not a human anymore. This alone is hugely disruptive as customer service touches so many verticals. It's already happening and will obviously only continue - especially when you talk to a service agent on the phone, increasingly it will be an LLM text-to-speech agent.

- llama.cpp/Ollama/HF & cloud services like Replicate: Infra for companies to run their own models instead of using Open AI due to cost/limitations. Obvious benefit for companies is you just want to pay for the compute you use, not for a consumer product like ChatGPT that abstracts away the usage - Open AI gets very expensive very quickly if using it on behalf of an application with many users. Also for niche use cases it might not be possible to accomplish what you want as an Open AI customer, you might need more control over models.

- Midjourney/Stable Diffusion type models: Totally separate from LLMs and language, there are diffusion models on image generation sites like LeonardoAI for creating concept art, illustrations, photography, and other visuals. There is a lot of obvious value here for creative work - it could displace a lot of conventional services and change the way we think about and pay for applied art. It's controversial in the way mp3s were, which itself will spawn some innovation in the legal space and in the way we interact with creative content.

- Self-driving cars: People are already taking the rides. AI modeling will continue to play a huge role in automating personal transit, and also for fleets. There will be self-delivering food, mail, and freight.

Particularly promising areas considering other modalities and fine-tunes:

- Music generation - Film (imagine prompt-2-film) - Extremely accurate/good legal advice where there are no flaws in your case - Medical diagnoses/analyses that are highly specific to your body and full of info and visuals particular to your condition - Negotiation AI for buying/selling, signing contracts for jobs or legal settlements, and general payments/invoicing - General automation ("Call the DMV and ask about my license", "Call the auto shop, don't let them upsell any services") - All the tech needed to integrate this stuff in the best ways